Parallel Learning Evolutionary Algorithm Based on Neural Network Ensemble

A new parallel evolutionary algorithm based on neural network (NN) ensemble is proposed for mobile robots. The robot controller has a reconfigurable structure with user- defined sensor suite, which corresponds to a typical network. NN ensemble is evolved to optimize the optimal sub-networks including both learning rules and combining weights dynamically. The experiment results show that the genetic algorithm based NN ensemble has stronger evolutionary capacity and higher learning efficiency of parallelism compared with the general genetic algorithm.